Business - Supply Chain Manufacturing Operations Solution - Senior Manager - Consulting

Location:

Anywhere in Country

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As a Solution Senior Manager in Supply Chain Manufacturing Operations, you will lead the design, build, testing, and scaling of differentiated AI-enabled manufacturing solutions. You will combine deep manufacturing and supply chain domain knowledge with manufacturing data platforms, industrial data architectures, predictive and generative AI, knowledge graphs, retrieval-augmented generation (RAG), data ontologies, and reusable application components

This is a senior, hands‑on solution leadership role. The primary purpose of the position is to set direction and lead teams that create working solutions, prototypes, accelerators, demonstrations, reference architectures, and reusable intellectual property that can be configured and deployed by pursuit and delivery teams.

You will lead and collaborate with manufacturing practitioners, Managers, data engineers, data scientists, AI engineers, software developers, architects, alliance teams, and solution leaders to turn priority manufacturing use cases into production‑oriented solution assets. You will be accountable for solution strategy, technical credibility, quality and risk management, commercial relevance, talent development, repeatability, and adoption across the practice.

As a Solution Senior Manager in Supply Chain Manufacturing Operations, you will be responsible for the strategy, portfolio direction, and end‑to‑end development of AI-enabled manufacturing solutions and the reusable data and technology foundations required to scale them across pursuits and engagements.

• Set the vision, roadmap, investment priorities, and quality standards for a portfolio of AI-enabled manufacturing solutions, prototypes, accelerators, demonstrations, and reusable solution components.
• Lead Managers and multidisciplinary teams through concept definition, architecture, build, testing, release, adoption, and continuous improvement while remaining sufficiently hands‑on to challenge technical decisions and resolve critical issues.
• Translate manufacturing and supply chain priorities into compelling AI use cases, value hypotheses, user stories, functional and technical requirements, data and model requirements, acceptance criteria, and measurable operational outcomes.
• Own solution governance, including architecture decisions, responsible AI, cybersecurity, data privacy, quality, risk, release readiness, documentation, and compliance with firm development standards.
• Direct the design of manufacturing data platforms that connect and contextualize data from MES/MOM, ERP, historians, SCADA, PLC, IoT, quality, maintenance, laboratory, warehouse, engineering, document, image, and enterprise systems.
• Guide the development of reusable manufacturing data models, ontologies, semantic layers, taxonomies, metadata, entity relationships, knowledge graphs, and governance standards spanning assets, products, materials, production, quality, maintenance, inventory, energy, labor, and performance.
• Lead the design and industrialization of RAG and GraphRAG solutions using governed manufacturing content, operational data, embeddings, vector search, knowledge graphs, metadata filtering, evaluation methods, guardrails, and human oversight.
• Shape AI assistants, copilots, agents, predictive models, and intelligent workflows for use cases such as predictive maintenance, anomaly detection, root‑cause analysis, quality investigation, production optimization, shift handover, troubleshooting, energy…